NXP backend: Replace CustomDelegationOptions with NeutronTargetSpec in new Neutron C flow references

Author: StrycekSimon

backends/nxp/backend/custom_delegation_options.py

@@ -22,7 +22,3 @@ class CustomDelegationOptions:
     #  not create any NeutronGraph that can be called. This is done by the partitioner itself, and is not handled by
     #  the individual node converters.
     allow_no_op_partitions: bool = False
-
-    # The new neutron converter flow has different constraints for supported operators. These need to be addressed when
-    # deciding is operator is delegated or not in _is_supported_on_target().
-    use_new_flow_neutron_c: bool = False

backends/nxp/backend/ir/converter/node_converters/ops_converters/abs_converter.py

@@ -5,7 +5,6 @@
 
 
 import torch
-
 from executorch.backends.nxp.backend.ir.converter.node_converter import (
     CustomDelegationOptions,
     NeutronTargetSpec,
@@ -36,7 +35,7 @@ def _is_supported_on_target(
         custom_delegation_options: CustomDelegationOptions,
     ) -> bool:
 
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             supported_types = [torch.int8, torch.uint8]

backends/nxp/backend/ir/converter/node_converters/ops_converters/adaptive_avg_pool_2d_converter.py

@@ -78,7 +78,7 @@ def _is_supported_on_target(
             AdaptiveAvgPool2dConverter._get_equivalent_avg_pool_parameters(node)
         )
 
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             if not NodeConverter.uses_quantization_type_for_io(

backends/nxp/backend/ir/converter/node_converters/ops_converters/add_tensor_converter.py

@@ -26,7 +26,7 @@ def _is_supported_on_target(
         parameters_mapping: dict[str, Parameter],
         custom_delegation_options: CustomDelegationOptions,
     ) -> bool:
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             if not NodeConverter.at_least_one_input_shape_matches_the_output_shape(
                 node
             ):

backends/nxp/backend/ir/converter/node_converters/ops_converters/avg_pool_2d_converter.py

@@ -5,7 +5,6 @@
 
 import numpy as np
 import torch
-
 from executorch.backends.nxp.backend.ir.converter.conversion import (
     aten_translator,
     common,
@@ -22,7 +21,6 @@
 from executorch.backends.nxp.backend.ir.tflite_generator.builtin_options import (
     average_pool_2d_options,
 )
-
 from executorch.backends.nxp.backend.neutron_target_spec import NeutronTargetSpec
 from torch.fx import Node
 from torch.nn import Parameter
@@ -66,7 +64,7 @@ def _is_supported_on_target(
         kernel = node.args[1]
         stride = node.args[2]
 
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             supported_types = [torch.int8, torch.uint8]

backends/nxp/backend/ir/converter/node_converters/ops_converters/constant_pad_nd_converter.py

@@ -42,7 +42,7 @@ def _is_supported_on_target(
         parameters_mapping: dict[str, Parameter],
         custom_delegation_options: CustomDelegationOptions,
     ) -> bool:
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             if not NodeConverter.uses_quantization_type_for_io(

backends/nxp/backend/ir/converter/node_converters/ops_converters/leaky_relu_converter.py

@@ -35,7 +35,7 @@ def _is_supported_on_target(
         parameters_mapping: dict[str, Parameter],
         custom_delegation_options: CustomDelegationOptions,
     ) -> bool:
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             if not NodeConverter.uses_quantization_type_for_io(

backends/nxp/backend/ir/converter/node_converters/ops_converters/max_pool2d_with_indices_converter.py

@@ -7,7 +7,6 @@
 
 import numpy as np
 import torch
-
 from executorch.backends.nxp.backend.edge_helper import try_get_arg
 from executorch.backends.nxp.backend.ir.converter.conversion import (
     aten_translator,
@@ -74,7 +73,7 @@ def _is_supported_on_target(
             MaxPool2DWithIndicesConverter._get_node_args(node)
         )
 
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             supported_types = [torch.int8, torch.uint8]

backends/nxp/backend/ir/converter/node_converters/ops_converters/mean_dim_converter.py

@@ -38,7 +38,7 @@ def supports_partitioning_result(
         neutron_target_spec: NeutronTargetSpec,
         parameters_mapping: dict[str, Parameter],
     ) -> bool:
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             dim, keepdim = MeanDimConverter._get_attrs(node)
             input_shape = node.args[0].meta["val"].shape
 
@@ -64,7 +64,7 @@ def _is_supported_on_target(
         parameters_mapping: dict[str, Parameter],
         custom_delegation_options: CustomDelegationOptions,
     ) -> bool:
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             # Requirements specified by the new Neutron flow documentation.
 
             if not NodeConverter.uses_quantization_type_for_io(

backends/nxp/backend/ir/converter/node_converters/ops_converters/mul_tensor_converter.py

@@ -4,7 +4,6 @@
 # LICENSE file in the root directory of this source tree.
 
 import torch
-
 from executorch.backends.nxp.backend.data_format import NXP_NODE_FORMAT
 from executorch.backends.nxp.backend.ir.converter.node_converter import (
     CustomDelegationOptions,
@@ -26,7 +25,7 @@ def _is_supported_on_target(
         parameters_mapping: dict[str, Parameter],
         custom_delegation_options: CustomDelegationOptions,
     ) -> bool:
-        if custom_delegation_options.use_new_flow_neutron_c:
+        if neutron_target_spec.use_new_flow_neutron_c:
             if not NodeConverter.at_least_one_input_shape_matches_the_output_shape(
                 node
             ):